Time-of-flight sensor and color camera calibration for multi-view acquisition

This paper presents a multi-view acquisition system using multi-modal sensors, composed of time-of-flight (ToF) range sensors and color cameras. Our system captures the multiple pairs of color images and depth maps at multiple viewing directions. In order to ensure the acceptable accuracy of measurements, we compensate errors in sensor measurement and calibrate multi-modal devices. Upon manifold experiments and extensive analysis, we identify the major sources of systematic error in sensor measurement and construct an error model for compensation. As a result, we provide a practical solution for the real-time error compensation of depth measurement. Moreover, we implement the calibration scheme for multi-modal devices, unifying the spatial coordinate for multi-modal sensors. The main contribution of this work is to present the thorough analysis of systematic error in sensor measurement and therefore provide a reliable methodology for robust error compensation. The proposed system offers a real-time multi-modal sensor calibration method and thereby is applicable for the 3D reconstruction of dynamic scenes.     

Compression Domain Volume Rendering for Distributed Environments

This paper describes a method for volume data compression and rendering which bases on wavelet splats. The underlying concept is especially designed for distributed and networked applications, where we assume a remote server to maintain large scale volume data sets, being inspected, browsed through and rendered interactively by a local client. Therefore, we encode the server’s volume data using a newly designed wavelet based volume compression method. A local client can render the volumes immediately from the compression domain by using wavelet footprints, a method proposed earlier. In addition, our setup features full progression, where the rendered image is refined progressively as data comes in. Furthermore, framerate constraints are considered by controlling the quality of the image both locally and globally depending on the current network bandwidth or computational capabilities of the client. As a very important aspect of our setup, the client does not need to provide storage for the volume data and can be implemented in terms of a network application. The underlying framework enables to exploit all advantageous properties of the wavelet transform and forms a basis for both sophisticated lossy compression and rendering. Although coming along with simple illumination and constant exponential decay, the rendering method is especially suited for fast interactive inspection of large data sets and can be supported easily by graphics hardware.     

Preserving Topology by a Digitization Process

The main task of digital image processing is to recognize properties of real objects based on their digital images. These images are obtained by some sampling device, like a CCD camera, and represented as finite sets of points that are assigned some value in a gray-level or color scale. Based on technical properties of sampling devices, these points are usually assumed to form a square grid and are modeled as finite subsets of Z². Therefore, a fundamental question in digital image processing is which features in the digital image correspond, under certain conditions, to properties of the underlying objects. In practical applications this question is mostly answered by visually judging the obtained digital images. In this paper we present a comprehensive answer to this question with respect to topological properties. In particular, we derive conditions relating properties of real objects to the grid size of the sampling device which guarantee that a real object and its digital image are topologically equivalent. These conditions also imply that two digital images of a given object are topologically equivalent. This means, for example, that shifting or rotating an object or the camera cannot lead to topologically different images, i.e., topological properties of obtained digital images are invariant under shifting and rotation.     

Numerical Modeling of Grain Boundary Effects in the Diffusional Creep of Copper Interconnect Lines

We propose a numerical simulation technique to model the process of diffusional creep and stress relaxation that occurs in Cu-damascene interconnects of integrated circuit devices in processing stage. The mass flow problem is coupled to the stress analysis through vacancy flux and equilibrium vacancy concentration. The technique is implemented in a software package that seamlessly integrates the problem-oriented code with commercially available finite element program MSC.Marc. It is utilized to model the Coble creep phenomenon by introducing the nanoscale grain boundary region having the thickness on the order of several layers of atoms. As an illustration, the two-dimensional problem of stress relaxation in a single grain subjected to prescribed displacements and tractions is examined.     

Intramyocardial Inflammation after COVID-19 Vaccination: An Endomyocardial Biopsy-Proven Case Series

Myocarditis in response to COVID-19 vaccination has been reported since early 2021. In particular, young male individuals have been identified to exhibit an increased risk of myocardial inflammation following the administration of mRNA-based vaccines. Even though the first epidemiological analyses and numerous case reports investigated potential relationships, endomyocardial biopsy (EMB)-proven cases are limited. Here, we present a comprehensive histopathological analysis of EMBs from 15 patients with reduced ejection fraction (LVEF = 30 (14–39)%) and the clinical suspicion of myocarditis following vaccination with Comirnaty^® (Pfizer-BioNTech) (n = 11), Vaxzevria^® (AstraZenica) (n = 2) and Janssen^® (Johnson & Johnson) (n = 2). Immunohistochemical EMB analyses reveal myocardial inflammation in 14 of 15 patients, with the histopathological diagnosis of active myocarditis according the Dallas criteria (n = 2), severe giant cell myocarditis (n = 2) and inflammatory cardiomyopathy (n = 10). Importantly, infectious causes have been excluded in all patients. The SARS-CoV-2 spike protein has been detected sparsely on cardiomyocytes of nine patients, and differential analysis of inflammatory markers such as CD4⁺ and CD8⁺ T cells suggests that the inflammatory response triggered by the vaccine may be of autoimmunological origin. Although a definitive causal relationship between COVID-19 vaccination and the occurrence of myocardial inflammation cannot be demonstrated in this study, data suggest a temporal connection. The expression of SARS-CoV-2 spike protein within the heart and the dominance of CD4⁺ lymphocytic infiltrates indicate an autoimmunological response to the vaccination.     

BetweenIT: An Interactive Tool for Tight Inbetweening

The generation of inbetween frames that interpolate a given set of key frames is a major component in the production of a 2D feature animation. Our objective is to considerably reduce the cost of the inbetweening phase by offering an intuitive and effective interactive environment that automates inbetweening when possible while allowing the artist to guide, complement, or override the results. Tight inbetweens, which interpolate similar key frames, are particularly time‐consuming and tedious to draw. Therefore, we focus on automating these high‐precision and expensive portions of the process. We have designed a set of user‐guided semi‐automatic techniques that fit well with current practice and minimize the number of required artist‐gestures. We present a novel technique for stroke interpolation from only two keys which combines a stroke motion constructed from logarithmic spiral vertex trajectories with a stroke deformation based on curvature averaging and twisting warps. We discuss our system in the context of a feature animation production environment and evaluate our approach with real production data.     

Application of remote sensing to parks and protected area monitoring: Introduction to the special issue

This special issue is the result of sustained and highly collaborative efforts to improve the use of remotely sensed data to inform management of protected areas. The 15 papers in the issue address a diverse range of topics. These papers provide a conceptual basis and a framework for establishing monitoring programs, techniques and methods to make operational the use of remotely sensed data, case studies, and synthesis papers liking remotely sensed data to models used to inform ecological assessments. Studies in this issue necessarily confront the universal challenges of scale, both spatial and temporal, and the sometimes tenuous link between observed patterns and significant ecological process. A clear message is that the information needs of resource managers require information across scales, and these information demands will continue to motivate advances in the collection and analysis of remotely sensed data. This compilation of papers is unusual in (1) articulating a basic, if somewhat technical, foundation of remote sensing that is required for resource managers to effectively collaborate with remote sensing specialists, and (2) providing a framework for addressing monitoring resource issues that is likely to be of interest to many remote sensing specialists. We hope these papers inspire broader use of remotely sensed data to manage the increasingly rare and valuable resources in protected areas around the world.